Bargaining agents based system for automatic classification of potential allergens in recipes

Autor: Alemany-Bordera, José, Heras Barberá, Stella María, Palanca Cámara, Javier, Julian Inglada, Vicente Javier
Jazyk: angličtina
Rok vydání: 2016
Předmět:
Persuasion
Computer science
media_common.quotation_subject
BIBLIOTECONOMIA Y DOCUMENTACION
02 engineering and technology
Recommender system
Informótica
lcsh:QA75.5-76.95
Recommendation system
recommendation system
Intolerances
Food allergy
multi-agent system
0202 electrical engineering
electronic engineering
information engineering
Social information
General Environmental Science
Social influence
media_common
food allergy
business.industry
Recipe
General Engineering
Computing
020207 software engineering
Computación
Data science
Negotiation
Multi-agent system
Order (business)
General Earth and Planetary Sciences
020201 artificial intelligence & image processing
lcsh:Electronic computers. Computer science
Artificial intelligence
business
Information Technology
LENGUAJES Y SISTEMAS INFORMATICOS
Zdroj: Advances in Distributed Computing and Artificial Intelligence Journal, Vol 5, Iss 2, Pp 43-51 (2016)
GREDOS. Repositorio Institucional de la Universidad de Salamanca
instname
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Popis: [EN] The automatic recipe recommendation which take into account the dietary restrictions of users (such as allergies or intolerances) is a complex and open problem. Some of the limitations of the problem is the lack of food databases correctly labeled with its potential allergens and non-unification of this information by companies in the food sector. In the absence of an appropriate solution, people affected by food restrictions cannot use recommender systems, because this recommend them inappropriate recipes. In order to resolve this situation, in this article we propose a solution based on a collaborative multi-agent system, using negotiation and machine learning techniques, is able to detect and label potential allergens in recipes. The proposed system is being employed in receteame.com, a recipe recommendation system which includes persuasive technologies, which are interactive technologies aimed at changing users’ attitudes or behaviors through persuasion and social influence, and social information to improve the recommendations
This work was supported by the projects TIN2015-65515-C4-1-R and TIN2014-55206-R of the Spanish government and by the grant program for the recruitment of doctors for the Spanish system of science and technology (PAID-10-14) of the Universitat Politecnica de Valencia.
Databáze: OpenAIRE
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